Case ReportPublished framework studyJun. 2025
AAB-CASE-2025-RV-042
Developing a Holistic AI Literacy Framework for Children
HK PolyU-led; ACM Trans. Comput. Educ. 2025.
This page documents an AI literacy or AI education case for registry purposes. It is descriptive and does not imply AAB endorsement of any specific tool, provider, or intervention.
01
Implementation
Hong Kong universities (PolyU, HKUST, EdUHK)
02
Learning context
In-school (K–12)
03
AI role
Tutor
04
Outcome signal
Curriculum guidance
Registry Facets
0
Education Level
- K-12
- Pre-K
Subject Area
- AI literacy
Use Case Type
- Framework development
Stakeholder Group
- Researchers
- Practitioners
AI Capability Type
- Foundational AI concepts
- Ethics
Implementation Model
- Cross-cutting
Evidence Type
- Systematic review
Outcomes Domain
- Curriculum guidance
Implementing Organization
1
Organization Type
Hong Kong universities (PolyU, HKUST, EdUHK)
Location
Hong Kong SAR, China
Primary Facilitator Role
Authors systematic synthesis
Learning Context
2
Setting Type
- In-school (K–12)
- Informal learning
Session Format
Systematic literature search of children’s AI interventions
Duration
Corpus per methods section
Group Size
Many studies synthesized
Devices
Curricula, workshops, tools across corpus
Constraints
- Field evolves quickly
- Breadth/depth tradeoffs in coding
Learner Profile
3
Age Range
Children (kindergarten–secondary)
Prior AI Exposure Assumed
Increasing
Prior Programming Background Assumed
Varies
Educational Intent
4
Primary Learning Goals
- Answer what content constitutes children’s AI literacy
- Unify eight areas under three dimensions
Secondary Learning Goals
- Support designers and educators
What This Was Not
- Not RCT of one curriculum
AI Tool Description
5
Tool Type
Framework (not single tool)
AI Role
- Tutor
Languages
Global literature in search
User Interaction Model
- Maps awareness/mechanics/impacts
Safeguards
- Responsible practice as explicit pillar
Activity Design
6
Activity Flow
- Systematic search
- Extract practices
- Build framework
Human Vs AI Responsibilities
Scaffolding Strategies
Observed Challenges
7
Educators Reported
- Inconsistent intervention breadth/depth in field
- Lack of consensus before framework
Design Adaptations
8
Adaptations
- Holistic three-dimensional child-specific structure
Reported Outcomes
9
Engagement
Learning Signals
Educators Reflection
Practical mapping tool for next-gen AI education content.
Ethical & Privacy Considerations
10
Privacy
- Child data ethics in cited interventions
- GenAI updates after publication
Evidence Type
11
Evidence
- Activity documentation
- Practitioner observation
Relevance to Research
12
Potential Research Use
- Validate framework with assessments
- Localize frameworks culturally
Relevant Research Domains
- AI literacy
- Curriculum design
Case Status
13
Case Status
- Completed
AAB Classification Tags
14
Age
Children
Setting
Formal+informal
AI Function
Literacy content map
Pedagogy
Framework
Risk Level
Low
Data Sensitivity
N/A
Registry Metadata
15
Case ID
AAB-CASE-2025-RV-042
Publication Status
Published framework study
Tags
caseK-12Hong Kong SAR, ChinaCross-cuttingFoundational AI conceptsAI literacyFramework development